VC PhD Scholarships: ACEGES project

Proposal 1- Energy-Economy-Investment Modelling: Volatility of oil prices and oil supply
Applications are invited in the area of Energy-Economy-Investment Modelling. The applications should be within the scope of the ACEGES project (http://www.londonmet.ac.uk/lmbs/research/cibs/cibs-scenario-planning/cibs-scenario-planning_home.cfm).

In particular, we encourage applications that aim to investigate the relationships between:
i) Spot price of crude oil,
ii) Expectations of future oil prices
iii) Price of crude oil futures
iv) Oil futures spread (defined as the percent deviation of the oil futures price from the spot price of oil)
v) Oil supply shocks.

The overall research aim is to investigate what determines the spot and futures price of crude oil and the importance of the evolution of the price of oil in explaining oil production of OPEC and non-OPEC countries.

Applicants are expected to have a Master’s degree with a strong quantitative, mathematical or statistical focus. Programming experience in Java and/or R is desirable but not essential.

References:
1) Hamilton, J. (2003), What is an Oil Shock? Journal of Econometrics, vol. 113(2), 363-398
2) Alquist, R and Kilian, L. (2010), What Do We Learn from the Price of Crude Oil Futures? Journal of Applied Econometrics, 25(4), 539-573.
3) Kaufmann, R.K. (1991), Oil production in the lower 48 states: Reconciling curve fitting and econometric models. Resources and Energy, 13(1), 111-127

In the first instance, contact me at v.voudouris@londonmet.ac.uk

Proposal 2 - Consumer decision-making and social interaction at the movies: The Philadelphia Story
When faced with choices between new products and services, the properties of which are uncertain, how do individuals behave? Economists commonly distinguish between social and private information available to the consumer - social learning takes place through social networks, while private learning is the consequence of past experience. In factoring both into the decision-making process it is possible to model consumer behaviour - in this instance film consumer behaviour.

To do this I propose developing an agent-based model, which allows the researcher to investigate the microscopic behaviour of individual film consumers who watched particular films at particular cinemas at particular moments in time in order to a) grow the macroscopic environment manifest in the long tail distribution of revenue, b) chart the pattern of diffusion from box-office rich to box-office poor cinemas, and c) forecast the closing box-office of films that opened in the first-run cinemas from the opening Saturday night of the release.

The dataset that forms the basis of this proposal is drawn from the city of Philadelphia for the years 1935-36. Housed in the Warner Bros. Archive at the University of Southern California, I have recently uncovered the weekly billing sheets of 91 cinemas located in the city belonging to the Stanley Warner chain. The sheets provide micro data of an unparalleled nature about audience choices, consisting of daily box-office returns generated by the films screened at the 91 cinemas. This body of data has never previously been accessed. Once transcribed onto a database and analysed, it will make possible a much fuller understanding of audiences and the choices they made. Furthermore, the work will be directly applicable to contemporary consumer behaviour concerning experience goods.

I am looking for a graduate student that has an excellent quantitative historical background, who is excited about executing detailed fieldwork in the city of Philadelphia; building a dataset from archive materials using relational database software; and finally modelling the data to investigate consumer behaviour. Knowledge of a programming language is desirable.

ACEGES Software: video- World Oil Production

Below is video of World Oil Production for 5 Monte Carlo experiments. The first graphic is a stacked timeseries representing the contribution of each country - only countries that produce for the specific experiment are shown. The second graphic is shows oil production and reserve/production ration. I thank Maciej M. Latek for his help in the design of the graphics.

The first simulated year is 2002.


A better quality video can be seen at:
http://screencast.com/t/OWM4YzkzYz

ACEGES Software: video

Although this is not a good video (not sure how to convert swf to mpeg), it show the 'world oil production' and the production of 'Saudi Arabia' for certain Monte Carlo Experiments of the ACEGES.

The lines with the 'left colors' show the 'Production' and the lines with the 'right colors' shows the 'Remaining Reserves/Production'.

NOTE: the world oil production has not been modelled explicitly. This is the macro-regularity of the decisions made by the agents - the 93 countries modeled in ACEGES 1.0.



When the graphics show different combinations of colors, this signals a new simulation with different starting assumptions for key uncertain variables such as EUR, peak/decline point and oil demand.

The ACEGES Project: Presentation

This is a general presentation that I give about the ACEGES project.

ACEGES Software: Probabilistic Forecasts of World Oil Production to 2100

I have been asked by a few people to show a graphic of World Oil Production. This is given in the figures below. I have superimposed the 'peak year' based upon the simulation (Monte Carlo simulations based upon distributional assumptions of OIL EUR, Peak Point, Oil Demand).

Although the peak year and peak production contradict much of the existing views, a full explanation of the assumptions of the ACEGES program and the data used to initialize the simulations will be provided in the ACEGES 1.0 manual - expected by the end of July. The figures are based on only 134 simulations.



The blue dots is a random sample from the simulated data and the black lines (in the figure below) are estimated centiles using the Generalized Beta type 2 distribution. All the four parameters of the distribution were modelled using cubic smoothing splines. The actual production, red line, seems to follow the 2% centile value.

ACEGES Software: Smooth Centile Curves for United States

Below is the centile curves of the simulated oil production data for the United States. The distribution used for the centile curves is the Box-Cox t where all the four parameters (mu-location, sigma-scale, nu-skewness, tau-kurtosis) of the distribution were modelled (in GAMLSS) using a non-parametric Penalised Beta Spline.


Currently, we are fitting additional distributions to see if we can capture better the skewness and kurtosis of the simulated data as the above centiles are wobbly.

ACEGES Software: World Oil Production

The figures below show the simulated world oil production where simulation step 0 means year 2002. Note that the world oil production has not been modelled explicitly. The world oil production is the emergent pattern of the production behavior of the individual countries (agents). Even though these figures shows a few simulations (each line represents a single simulation), there is an interesting clustering of peak year and peak oil production.

ACEGES Software: Results for IRAN

Below are 4 figures of simulated data for Iran (black line is the actual production). The first (log representation) and third figures are based on Monte Carlo simulations of EUR, Peak Point and Demand while the second (log representation) and fourth figures are based on Monte Carlo simulations of EUR and Demand.

NOTE: These results are based on less than 100 simulations. Therefore, at this stage these figures should be treated as cartoons!

ACEGES software: Smoothing the Monte Carlo Oil Production data

Following from my last posting, these are some figures (Ecuador & US out of the 93 countries modeled) of the simulated data, generated using the ACEGES software and analysed using the R statistics software.

Black line is the actual production, blue dots is a sample of the 3.2 million (simulated) records (see last figure - US) and the density is based on the whole 'population' of the 3.2 million records.

ACEGES software: Preliminary Results

I have recently completed the ACEGES 1.0 software. This is an agent-based model of conventional oil production for 93 countries.

Due to the uncertainties with the EUR data and the oil demand, I implemented a Monte Carlo simulation that uses distributional assumptions of EUR data and oil demand based upon the data released from the Energy Information Administration, International Energy Agency, CIA and the US Geological Survey.

Next month, I will finish the User Guide and I will post the software on the CIBS website: http://www.londonmet.ac.uk/lmbs/research/cibs/cibs-scenario-planning/cibs-scenario-planning_home.cfm . If you want to access it earlier, please email me at v.voudouris@lodonmet.ac.uk

THe figure below sow the results from the US & Kuwait . RED line is the actual production while the black dots are the simulated data (77 simulation runs of 99 steps).

The ACEGES project: An ACE Model for the Availability of Global Conventional Oil Supply

I will present a paper at the 16th International Conference on computing in economics and finance. The abstract is given below:

The overall aim of this paper is to present a developing agent-based computational laboratory, termed the ACEGES (Agent-based Computational Economics of the Global Energy System) laboratory, for the systematic experimental study of the global energy system through the mechanism of Energy Scenarios. In particular, our intention is to show how Agent-based Computational Economics (ACE) and the Generalized Additive Models for Location Scale and Shape (GAMLSS) can be fused to help us understand better the challenging outlook for conventional oil supply by means of controlled computational experiments.

Specifically, the ACEGES laboratory, which is developed using the MASON (Multi-Agent Simulator Of Networks) library and the R software, models oil production curves to analyse the energy supply tensions at the national level. These production curves are semi-parametric regression models of i) original extractable oil, ii) remaining oil prior to the previous year’s production, iii) previous year cumulative production iv) previous year consumption and v) the net world demand left after an estimated demand increase, which can only be satisfied by Pre-peak Net Producer (PPNP) agent.


These semiparametric regression models are developed using the GAMLSS framework, which allows us to express macrovariables as statistical distributions. GAMLSS is a general framework of regression type of modelling in which the response variable can have a very general (up to four parameters) distribution and all of the parameters of the distributions can be modelled as linear or smooth functions of the explanatory variables. Thus, the R-based GAMLSS tool is used to build oil production curves, which are used as the decision rules of the agents. This also reflects that the R-based GAMLSS tool is integrated with the ACEGES laboratory as a way of providing a methodological advancement to undertake rigorous study of economic systems.

The Secret Life of Chaos at BBC iPlayer

Chaos theory has a bad name, conjuring up images of unpredictable weather, economic crashes and science gone wrong. But there is a fascinating and hidden side to Chaos, one that scientists are only now beginning to understand.

It turns out that chaos theory answers a question that mankind has asked for millennia - how did we get here?

In this documentary, Professor Jim Al-Khalili sets out to uncover one of the great mysteries of science - how does a universe that starts off as dust end up with intelligent life? How does order emerge from disorder?

It's a mindbending, counterintuitive and for many people a deeply troubling idea. But Professor Al-Khalili reveals the science behind much of beauty and structure in the natural world and discovers that far from it being magic or an act of God, it is in fact an intrinsic part of the laws of physics. Amazingly, it turns out that the mathematics of chaos can explain how and why the universe creates exquisite order and pattern.

And the best thing is that one doesn't need to be a scientist to understand it. The natural world is full of awe-inspiring examples of the way nature transforms simplicity into complexity. From trees to clouds to humans - after watching this film you'll never be able to look at the world in the same way again.

UNECE: Energy Security and the Financial Crisis

The UNECE Energy Weekfeatures the 18th Session of the Committee on Sustainable Energy (18-20 November), including anEnergy Security Dialogue: Impact of the Financial Crisis on Energy Industries. The annual session of the Committee will focus on the impact of the financial crisis on the volume and timing of energy sector investments and implications for energy security with the participation of executives and planners from major energy companies. There will also be presentations of views on public responses by government officials, including in some cases green economic stimulus plans among other measures to support energy industries.

The focus on energy security will continue during the working session, beginning with a survey of the major international organizations with projects and programmes on sustainable energy and energy security. The Committee will also review the work programme of its subsidiary expert groups and projects.

The programme of the 18th Session of the Committee is available at:http://www.unece.org/energy/se/pdfs/comm18/18th_EnComm_Prog.pdf

The Committee Session will be preceded by the Forum on Clean Electricity Investment and the Financial Crisis, to be held during the fourth session of the Ad Hoc Group of Experts on Cleaner Electricity Production from Coal and other Fossil Fuels (16-17 November). The Forum will address the interaction between changing technologies, evolving policy expectations and the existing and expected regulatory framework. Participants will evaluate progress in moving towards cleaner electricity production from fossil fuels, including the impact of the financial crisis and the status of large-scale projects which require a suitable regulatory framework to attract investment.

The programme of the Forum is available at: http://www.unece.org/energy/se/docs/clep_ahge4.html

An agent-based model might provide novel insights in supporting decision-making of energy-related issues. Do you know of groups/examples of agent-based models and spatial agent-based models?

ACE Research Area: Restructured Electricity Markets

ACE Research Area: Restructured Electricity Markets

http://www.econ.iastate.edu/tesfatsi/aelect.htm

The goal of this resource site is to encourage the study of restructured electricity systems from a perspective that adequately addresses both economic and engineering concerns. In line with this goal, stress is placed on research making use of powerful new agent-based computational modeling tools. These tools permit restructured electricity systems to be modeled as commercial networks of strategically interacting traders and regulatory agencies learning to operate through time over realistically rendered transmission grids.

Vlasios

UC Berkeley "Center for the Study of Energy Markets"

The UC Berkeley "Center for the Study of Energy Markets" has posted new working papers:

"Explaining the Price of Voluntary Carbon Offsets"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp193.pdf

"Doing Well by Doing Good? Green Office Buildings"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp192.pdf

"When it comes to Demand Response, is FERC its Own Worst Enemy?"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp191.pdf

"Taxes and Trading versus Intensity Standards: Second-Best Environmental Policies with Incomplete Regulation (Leakage) or Market Power"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp190.pdf

"The Implied Cost of Carbon Dioxide under the Cash for Clunkers Program"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp189.pdf

"Building Out Alternative Fuel Retail Infrastructure: Government Fleet Spillovers in E85"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp188.pdf

"What Do Emissions Markets Deliver and to Whom? Evidence from Southern California’s NOx Trading Program"
Download this paper in Adobe Acrobat format:http://www.ucei.berkeley.edu/PDF/csemwp186.pdf

Nature: Meltdown Modelling & Agent-based Models

Leigh Tesfatsion brought to my attention the two ABM-related articles published in Nature:

• Meltdown Modeling: Could Agent-Based Computer Models Prevent Another Financial Crisis?
• The Economy Needs Agent-Based Modelling

Links to download the articles:

• Mark Buchanan, "Meltdown Modeling: Could Agent-Based Computer Models Prevent Another Financial Crisis?" (pdf,1.2K), Nature, Vol. 460, August 6, 2009, 680-682.
  http://www.econ.iastate.edu/tesfatsi/MeltDownModeling.Nature080609.Buchanan.pd

• J. Doyne Farmer and Duncan Foley, "The Economy Needs Agent-Based Modelling" (pdf,922K), Nature, Vol. 460, August 6, 2009, 685-686 http://www.econ.iastate.edu/tesfatsi/EconomyNeedsABM.NatureAug2009.FarmerFoley.pdf

Vice Chancellor's 30 PhD Scholarships: Agent-based Energy Modelling

If anyone knows anyone who might be interested in PhD studentships, they are now on our web site: http://www.londonmet.ac.uk/research/the-graduate-school/vice-chancellors-phd-scholarships.cfm

An advert willappear in the Times Higher tomorrow. Details will also appear on findaphd.com and jobs.ac.uk in the near future.

Please bring to anyone's attention who might be interested, particularly the project "Energy Scenario Planning: An agent-based model of the availability of global conventional oil supply"

Ref: Hallock, J.L., Tharakan, P., Hall, C.A.S., Jefferson, M., Wei, Wu., 2004. Forecasting the limits to the availability and diversity of global conventional oil supply. Energy 29, 1673–1696.

Scenario Planning - internally consistent, sufficiently  relevant and detailed stories of what may occur in the future - has been  used as a strategic tool to cope with, but not to disguise, the  economics of uncertainty. As a qualitative framework, scenario planning  provides the ideas, elements and building blocks, which can be  communicated to leaders to allow them to cope more effectively with  uncertainty and change.   Due to the critical importance of oil to modern economic activity, and  oil’s non-renewable nature, it is extremely important to try to estimate  possible trajectories of future oil production while accounting for  uncertainties in resource estimates and demand growth. We are inviting  applications for a studentship to develop several alternate scenarios  for conventional oil supply for the period 2002-2060 using the novel  Agent-based Computational Economics (ACE) research methodology. ACE  provides a new and fundamental standard of explanation, in which one  ‘grows’ the macrophenomenon of interest (country-level oil supply),  given certain sets of microfoundations (e.g. resource availability,  future demand)  Using country-specific microfoundations of (i) the domestic consumption of oil, (ii) the projected growth rates of oil consumption,  (iii)the volume of oil originally present before any extraction (EUR),  (iv) the annual production for 2001, (v) the cumulative production to  date, and (vi)estimates of oil remaining to date, the project will  develop bottom-up simulations of county-level ‘peak oil production’

The successful applicant will be part of the ACEGES team: http://www.londonmet.ac.uk/lmbs/research/cibs/cibs-scenario-planning/cibs-scenario-planning_home.cfm

The ACEGES (Agent-based Computational Economics of the Global Energy System) Project

We launched today the webiste (http://www.londonmet.ac.uk/lmbs/research/cibs/cibs-scenario-planning_home.cfm )for the ACEGES Project.

The overall aim of this proposal is to develop, test and disseminate an agent-based computational laboratory for the systematic experimental study of the global energy system through the mechanism of Energy Scenarios. In particular, our intention is to show how Agent-based Computational Economics (ACE) can be applied to help leaders in government, business and civil society better understand the challenging outlook for energy through controlled computational experiments.

The Centre for International Business and Sustainability (CIBS) at London Metropolitan Business School (LMBS) and the Statistics, Operational Research and Mathematics Research Centre (STORM) are embarking on a major modelling exercise to support long-term UK policy analysis such as energy security and climate change. In particular the ACEGES laboratory will address the following questions:

1. How will prices affect the ratio of technically recoverable/economically extractable oil and gas reserves?
2. At what rate over time can the oil and gas from geographically dispersed nations be supplied to the marketplace?
3. How will country-level population, welfare and technological innovation affect primary-energy demand?
4. What is the environmental impact of different energy policies

Energy Challenges for Complexity Science

Below is a list of newly funded projects in the area of complexity science and energy (at various scale of analysis). 

• Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE): a Complexity Science-Based Investigation into the Smart Grid Concept http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G059969/1
  
• reventing wide-area blackouts through adaptive islanding of transmission networks http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G059101/1 and http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G060169/1
• SCALE (SMALL CHANGES LEAD TO LARGE EFFECTS): Changing Energy Costs in Transport and Location Policy http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G057737/1
  
• Future Energy Decision Making for Cities - Can Complexity Science Rise to the Challenge? http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G05956X/1 and http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/G059780/1

Improvise Visualisation: Visual analysis of simulations

This experimental visualization (improvise ) is being developed using Improvise for visual analysis of data produced by RimSim Pacific Rim simulation software.

RimSim Video

This can be an interesting way to 'understand' the relationship between the parameters and solution spaces of the simulations, including agent-based simulations.

Vlasios